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            <article class="content wrap" id="_content" data-uid="Keras.Layers.ConvLSTM2D">
  
  
  <h1 id="Keras_Layers_ConvLSTM2D" data-uid="Keras.Layers.ConvLSTM2D" class="text-break">Class ConvLSTM2D
  </h1>
  <div class="markdown level0 summary"><p>Convolutional LSTM. It is similar to an LSTM layer, but the input transformations and recurrent transformations are both convolutional.</p>
</div>
  <div class="markdown level0 conceptual"></div>
  <div class="inheritance">
    <h5>Inheritance</h5>
    <div class="level0"><span class="xref">System.Object</span></div>
    <div class="level1"><a class="xref" href="Keras.Keras.html">Keras</a></div>
    <div class="level2"><a class="xref" href="Keras.Base.html">Base</a></div>
    <div class="level3"><a class="xref" href="Keras.Layers.BaseLayer.html">BaseLayer</a></div>
    <div class="level4"><a class="xref" href="Keras.Layers.RNN.html">RNN</a></div>
    <div class="level5"><span class="xref">ConvLSTM2D</span></div>
  </div>
  <div classs="implements">
    <h5>Implements</h5>
    <div><span class="xref">System.IDisposable</span></div>
  </div>
  <div class="inheritedMembers">
    <h5>Inherited Members</h5>
    <div>
      <a class="xref" href="Keras.Layers.BaseLayer.html#Keras_Layers_BaseLayer_Set_Keras_Layers_BaseLayer___">BaseLayer.Set(BaseLayer[])</a>
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    <div>
      <a class="xref" href="Keras.Base.html#Keras_Base_InvokeStaticMethod_System_Object_System_String_System_Collections_Generic_Dictionary_System_String_System_Object__">Base.InvokeStaticMethod(Object, String, Dictionary&lt;String, Object&gt;)</a>
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    <div>
      <a class="xref" href="Keras.Base.html#Keras_Base_InvokeMethod_System_String_System_Collections_Generic_Dictionary_System_String_System_Object__">Base.InvokeMethod(String, Dictionary&lt;String, Object&gt;)</a>
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      <a class="xref" href="Keras.Base.html#Keras_Base_Item_System_String_">Base.Item[String]</a>
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      <a class="xref" href="Keras.Keras.html#Keras_Keras_Instance">Keras.Instance</a>
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      <a class="xref" href="Keras.Keras.html#Keras_Keras_keras2onnx">Keras.keras2onnx</a>
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  </div>
  <h6><strong>Namespace</strong>: <a class="xref" href="Keras.Layers.html">Keras.Layers</a></h6>
  <h6><strong>Assembly</strong>: Keras.dll</h6>
  <h5 id="Keras_Layers_ConvLSTM2D_syntax">Syntax</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public class ConvLSTM2D : RNN, IDisposable</code></pre>
  </div>
  <h3 id="constructors">Constructors
  </h3>
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  <span class="small pull-right mobile-hide">
    <a href="https://github.com/SciSharp/Keras.NET/blob/master/Keras/Layers/Recurrent.cs/#L528">View Source</a>
  </span>
  <a id="Keras_Layers_ConvLSTM2D__ctor_" data-uid="Keras.Layers.ConvLSTM2D.#ctor*"></a>
  <h4 id="Keras_Layers_ConvLSTM2D__ctor_System_Int32_System_Tuple_System_Int32_System_Int32__System_Tuple_System_Int32_System_Int32__System_String_System_String_System_Tuple_System_Int32_System_Int32__System_String_System_String_System_Boolean_System_String_System_String_System_String_System_Boolean_System_String_System_String_System_String_System_String_System_String_System_String_System_String_System_Boolean_System_Boolean_System_Boolean_System_Single_System_Single_Keras_Shape_" data-uid="Keras.Layers.ConvLSTM2D.#ctor(System.Int32,System.Tuple{System.Int32,System.Int32},System.Tuple{System.Int32,System.Int32},System.String,System.String,System.Tuple{System.Int32,System.Int32},System.String,System.String,System.Boolean,System.String,System.String,System.String,System.Boolean,System.String,System.String,System.String,System.String,System.String,System.String,System.String,System.Boolean,System.Boolean,System.Boolean,System.Single,System.Single,Keras.Shape)">ConvLSTM2D(Int32, Tuple&lt;Int32, Int32&gt;, Tuple&lt;Int32, Int32&gt;, String, String, Tuple&lt;Int32, Int32&gt;, String, String, Boolean, String, String, String, Boolean, String, String, String, String, String, String, String, Boolean, Boolean, Boolean, Single, Single, Shape)</h4>
  <div class="markdown level1 summary"><p>Initializes a new instance of the <a class="xref" href="Keras.Layers.ConvLSTM2D.html">ConvLSTM2D</a> class.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public ConvLSTM2D(int filters, Tuple&lt;int, int&gt; kernel_size, Tuple&lt;int, int&gt; strides = null, string padding = &quot;valid&quot;, string data_format = &quot;&quot;, Tuple&lt;int, int&gt; dilation_rate = null, string activation = &quot;tanh&quot;, string recurrent_activation = &quot;hard_sigmoid&quot;, bool use_bias = true, string kernel_initializer = &quot;glorot_uniform&quot;, string recurrent_initializer = &quot;orthogonal&quot;, string bias_initializer = &quot;zeros&quot;, bool unit_forget_bias = true, string kernel_regularizer = &quot;&quot;, string recurrent_regularizer = &quot;&quot;, string bias_regularizer = &quot;&quot;, string activity_regularizer = &quot;&quot;, string kernel_constraint = &quot;&quot;, string recurrent_constraint = &quot;&quot;, string bias_constraint = &quot;&quot;, bool return_sequences = false, bool go_backwards = false, bool stateful = false, float dropout = 0F, float recurrent_dropout = 0F, Shape input_shape = null)</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int32</span></td>
        <td><span class="parametername">filters</span></td>
        <td><p>Integer, the dimensionality of the output space (i.e. the number output of filters in the convolution).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Tuple</span>&lt;<span class="xref">System.Int32</span>, <span class="xref">System.Int32</span>&gt;</td>
        <td><span class="parametername">kernel_size</span></td>
        <td><p>An integer or tuple/list of n integers, specifying the dimensions of the convolution window.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Tuple</span>&lt;<span class="xref">System.Int32</span>, <span class="xref">System.Int32</span>&gt;</td>
        <td><span class="parametername">strides</span></td>
        <td><p>An integer or tuple/list of n integers, specifying the strides of the convolution. Specifying any stride value != 1 is incompatible with specifying any dilation_rate value != 1.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">padding</span></td>
        <td><p>One of &quot;valid&quot; or &quot;same&quot; (case-insensitive).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">data_format</span></td>
        <td><p>A string, one of &quot;channels_last&quot; (default) or &quot;channels_first&quot;. The ordering of the dimensions in the inputs. &quot;channels_last&quot; corresponds to inputs with shape (batch, time, ..., channels) while &quot;channels_first&quot; corresponds to inputs with shape (batch, time, channels, ...). It defaults to the image_data_format value found in your Keras config file at ~/.keras/keras.json. If you never set it, then it will be &quot;channels_last&quot;.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Tuple</span>&lt;<span class="xref">System.Int32</span>, <span class="xref">System.Int32</span>&gt;</td>
        <td><span class="parametername">dilation_rate</span></td>
        <td><p>An integer or tuple/list of n integers, specifying the dilation rate to use for dilated convolution. Currently, specifying any dilation_rate value != 1 is incompatible with specifying any strides value != 1.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">activation</span></td>
        <td><p>Activation function to use (see activations). If you don't specify anything, no activation is applied (ie. &quot;linear&quot; activation: a(x) = x).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">recurrent_activation</span></td>
        <td><p>Activation function to use for the recurrent step (see activations).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Boolean</span></td>
        <td><span class="parametername">use_bias</span></td>
        <td><p>Boolean, whether the layer uses a bias vector.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">kernel_initializer</span></td>
        <td><p>Initializer for the kernel weights matrix, used for the linear transformation of the inputs. (see initializers).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">recurrent_initializer</span></td>
        <td><p>Initializer for the recurrent_kernel weights matrix, used for the linear transformation of the recurrent state. (see initializers).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">bias_initializer</span></td>
        <td><p>Initializer for the bias vector (see initializers).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Boolean</span></td>
        <td><span class="parametername">unit_forget_bias</span></td>
        <td><p>Boolean. If True, add 1 to the bias of the forget gate at initialization. Use in combination with bias_initializer=&quot;zeros&quot;. This is recommended in Jozefowicz et al. (2015).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">kernel_regularizer</span></td>
        <td><p>Regularizer function applied to the kernel weights matrix (see regularizer).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">recurrent_regularizer</span></td>
        <td><p>Regularizer function applied to the recurrent_kernel weights matrix (see regularizer).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">bias_regularizer</span></td>
        <td><p>Regularizer function applied to the bias vector (see regularizer).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">activity_regularizer</span></td>
        <td><p>Regularizer function applied to the output of the layer (its &quot;activation&quot;). (see regularizer).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">kernel_constraint</span></td>
        <td><p>Constraint function applied to the kernel weights matrix (see constraints).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">recurrent_constraint</span></td>
        <td><p>Constraint function applied to the recurrent_kernel weights matrix (see constraints).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">bias_constraint</span></td>
        <td><p>Constraint function applied to the bias vector (see constraints).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Boolean</span></td>
        <td><span class="parametername">return_sequences</span></td>
        <td><p>Boolean. Whether to return the last output in the output sequence, or the full sequence.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Boolean</span></td>
        <td><span class="parametername">go_backwards</span></td>
        <td><p>Boolean (default False). If True, process the input sequence backwards.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Boolean</span></td>
        <td><span class="parametername">stateful</span></td>
        <td><p>Boolean (default False). If True, the last state for each sample at index i in a batch will be used as initial state for the sample of index i in the following batch.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Single</span></td>
        <td><span class="parametername">dropout</span></td>
        <td><p>Float between 0 and 1. Fraction of the units to drop for the linear transformation of the inputs.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Single</span></td>
        <td><span class="parametername">recurrent_dropout</span></td>
        <td><p>Float between 0 and 1. Fraction of the units to drop for the linear transformation of the recurrent state.</p>
</td>
      </tr>
      <tr>
        <td><a class="xref" href="Keras.Shape.html">Shape</a></td>
        <td><span class="parametername">input_shape</span></td>
        <td><p>The input shape.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h3 id="implements">Implements</h3>
  <div>
      <span class="xref">System.IDisposable</span>
  </div>
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